Chang’E-1(CE-1)Interference Imaging Spectrometer(IIM)dataset suffers from the weak response in the near infrared(NIR)bands,which are the important wavelength for retrieving the minerals and elements of the Moon.In th...Chang’E-1(CE-1)Interference Imaging Spectrometer(IIM)dataset suffers from the weak response in the near infrared(NIR)bands,which are the important wavelength for retrieving the minerals and elements of the Moon.In this paper,the cross-calibration was implemented to the IIM hyperspectral data for improving the weak response in NIR bands.The results show that the cross-calibrated IIM spectra were consistent to the Earth-based telescopic spectra,which suggests that the cross-calibration yields acceptable results.For further validating the influence of the cross-calibration on the FeO inversion and searching the optimal bands to retrieve lunar FeO contents,four band selection schemes were designed to retrieve FeO using the original and cross-calibrated IIM spectra.By comparing the distribution patterns and histograms of the IIM derived FeO contents with the Clementine derived FeO,the IIM 891 nm band after cross-calibration showed a higher accuracy in the FeO inversion,hence most useful for lunar FeO inversion.展开更多
One polythiophene derivative PT3T and two low band gap copolymers,PBTT-T3T and PBTT,with different ratios of 5,6-dini-trobenzothiadiazole as the acceptor unit in the polymer backbone have been synthesized by Pd-cataly...One polythiophene derivative PT3T and two low band gap copolymers,PBTT-T3T and PBTT,with different ratios of 5,6-dini-trobenzothiadiazole as the acceptor unit in the polymer backbone have been synthesized by Pd-catalyzed Stille-coupling polymerizations.Thermal stability,X-ray diffraction analyses,UV-vis absorption spectra,photoluminescence spectra and electrochemical properties of the copolymers were investigated.The band gap estimated from UV-vis-NIR spectra of the copolymers films varied from 1.39 to 1.94 eV.Among these copolymers,the films of PBTT-T3T and PBTT,which contain the 5,6-dinitrobenzothiadiazole unit,cover a broad wavelength range in the visible and near-infrared region from 400 to 1000 nm with the maximal peak absorption around 700 nm,which is exactly matched with the maximum in the photon flux of the sun.展开更多
Visible and near infrared spectroscopy is a non-destructive,green,and rapid technology that can be utilized to estimate the components of interest without conditioning it,as compared with classical analytical methods....Visible and near infrared spectroscopy is a non-destructive,green,and rapid technology that can be utilized to estimate the components of interest without conditioning it,as compared with classical analytical methods.The objective of this paper is to compare the performance of artificial neural network(ANN)(a nonlinear model)and principal component regression(PCR)(a linear model)based on visible and shortwave near infrared(VIS-SWNIR)(400-1000 nm)spectra in the non-destructive soluble solids content measurement of an apple.First,we used multiplicative scattering correction to pre-process the spectral data.Second,PCR was applied to estimate the optimal number of input variables.Third,the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN models.The initial weights and the number of hidden neurons were adjusted to optimize the performance of ANN.Findings suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.展开更多
基金supported by the National Basic Research Program of China (Grant No. 2010CB951603)Shanghai Science and Technology Support Program Special for EXPO (Grant No. 10DZ0581600)+2 种基金the Open Research Funding Program of KLGIS (Grant No. KLGIS2011A09)the National Natural Science Foundation of China (Grant No. 41172296)the Program for New Century Excellent Talents in University (Grant No. NCET-11-0242)
文摘Chang’E-1(CE-1)Interference Imaging Spectrometer(IIM)dataset suffers from the weak response in the near infrared(NIR)bands,which are the important wavelength for retrieving the minerals and elements of the Moon.In this paper,the cross-calibration was implemented to the IIM hyperspectral data for improving the weak response in NIR bands.The results show that the cross-calibrated IIM spectra were consistent to the Earth-based telescopic spectra,which suggests that the cross-calibration yields acceptable results.For further validating the influence of the cross-calibration on the FeO inversion and searching the optimal bands to retrieve lunar FeO contents,four band selection schemes were designed to retrieve FeO using the original and cross-calibrated IIM spectra.By comparing the distribution patterns and histograms of the IIM derived FeO contents with the Clementine derived FeO,the IIM 891 nm band after cross-calibration showed a higher accuracy in the FeO inversion,hence most useful for lunar FeO inversion.
基金support from the National Natural Science Foundation of China (50933003 & 50903044)MOST of China (2009AA032304)
文摘One polythiophene derivative PT3T and two low band gap copolymers,PBTT-T3T and PBTT,with different ratios of 5,6-dini-trobenzothiadiazole as the acceptor unit in the polymer backbone have been synthesized by Pd-catalyzed Stille-coupling polymerizations.Thermal stability,X-ray diffraction analyses,UV-vis absorption spectra,photoluminescence spectra and electrochemical properties of the copolymers were investigated.The band gap estimated from UV-vis-NIR spectra of the copolymers films varied from 1.39 to 1.94 eV.Among these copolymers,the films of PBTT-T3T and PBTT,which contain the 5,6-dinitrobenzothiadiazole unit,cover a broad wavelength range in the visible and near-infrared region from 400 to 1000 nm with the maximal peak absorption around 700 nm,which is exactly matched with the maximum in the photon flux of the sun.
基金Project(No.UTM.J.10.01/13.14/1/127/1 Jld 3(48))supported by the Zamalah Scholarship from the Universiti Teknologi Malaysia
文摘Visible and near infrared spectroscopy is a non-destructive,green,and rapid technology that can be utilized to estimate the components of interest without conditioning it,as compared with classical analytical methods.The objective of this paper is to compare the performance of artificial neural network(ANN)(a nonlinear model)and principal component regression(PCR)(a linear model)based on visible and shortwave near infrared(VIS-SWNIR)(400-1000 nm)spectra in the non-destructive soluble solids content measurement of an apple.First,we used multiplicative scattering correction to pre-process the spectral data.Second,PCR was applied to estimate the optimal number of input variables.Third,the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN models.The initial weights and the number of hidden neurons were adjusted to optimize the performance of ANN.Findings suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.
